When measuring the volume of ventricles, especially the right ventricle, the so called disc summation method is currently used as a gold standard. The inner contour of each of the ventricles will thereby be drawn into a stack of magnetic resonance tomography images and each of the volumes will be summed up. However, this method is time consuming and furthermore requires acquisition of costly magnetic resonance tomography (MRT) images. Contrary to that, ultra sound images of the heart, especially three dimensional (3D) or four dimensional (4D) echocardiographic images of the heart, wherein the fourth dimension is the time, are available, considerably easier and more cost effective.
In the established software of the applicant 4D RV-Function® during examination of the right ventricle by the user selection of three sectional planes across the 3D- or 4D-image data set, respectively, i.e. a sagittal plane, a four chamber view and a coronal plane, is required. Onto these images contours of the right ventricle will be drawn, occasionally with the help of the computer, but under the control of a user, and from there a surface model of the right ventricle is spanned, which then in turn will be used for the representation as well as calculation of important parameters of the heart function. The disadvantage with this process however resides in that the user is required to select sectional planes which he is not familiar with, especially the coronal plane. Furthermore in these planes contours of the right ventricle have to be defined. By doing this errors will readily arise, which are not easily realized by the user.
The publications U.S. Pat. No. 6,106,466 and US 2003/0038802 A1 each suggest processes for the adaptation of a surface of a part of a heart. In the process multiple images are acquired with ultra sound imaging in different image planes. In those images a user chooses specified points, i.e. generally at least three land marks, which are located on the surface to be modeled, and a surface model will then be adapted at those points. The disadvantage of this process however resides in that the user has to find the anatomical positions corresponding to the land marks via an appropriate navigation across the acquired ultra sound images, in order to be able to place the land marks. This occasionally may not be easy. Furthermore a corresponding point on the surface model then must be able to be assigned to each of the land marks. I.e. the land marks are a component of the surface model or are located on the surface, respectively. In this approach positioning errors will have a greater impact on the definition of the surface model upon defining the land marks the closer said land marks are located to each other. Ideally the latter will also be chosen such that on the one hand they may be reproducibly detected, but on the other hand will be located maximally spaced apart from each other. Both requirements collectively will strongly limit the selection of useful land marks.